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I am surprised daily about how many organizations can’t articulate how their improvement in various experience measures, like Net Promoter Score®, will benefit the organization. This connection is essential to understand to create a winning customer strategy. 

The same is true for customer data. Too often, an organization is excellent at collecting data to measure the effects of their efforts but has no idea how they will use it. A larger strategy for using your data is equally as crucial to your gained insights as improving experiences for customers is for connecting to your bottom line. 

The strategy for your collected data was the subject of a recent podcast. We spoke with Ryan Stuart (@rstuart85), Founder and CEO of Kapiche, a platform specializing in helping organizations use the data they have collected. Stuart understands the problems that can happen once you have a slew of customer insight but don’t know how to use it for your customer strategy or experience.  

Addressing this data-measurement use area is essential because there is a significant stagnation in customer satisfaction results today. For example, a recent report by the American Customer Satisfaction Index (ACSI) showed that only 30 percent of the businesses the ASCI tracked improved their Customer Satisfaction scores over the past ten years. That means 70 percent were either flat or declined. (To learn more about that situation, we hosted the ACSI’s managing director David VanAmburg in a recent podcast.) One of the contributing factors to these disappointing results is an overwhelming amount of data surrounding Customer Experiences—and it’s resulting in analysis paralysis instead of providing excellent customer strategy insights. In other words, people are doing what they think customers will like and measuring what happens in customer behavior, but then don’t know how to read the measurement data. As a result, they don’t know if their improvements to the experience are working. 

Building a Knowledge Pyramid

Stuart says that without a solid strategy around making the best use of the data that’s available to you, you can end up with a lot of answers to a question you don’t know to ask. Therefore, you can’t use the data. People collect the data because they know they should, and they genuinely care about how their organizations treat customers. However, without a strategy for measuring their results, they do not know what to do with it.  

To help organizations interpret their data, Stuart often drives the message of what he calls the “Knowledge Pyramid.” The concept behind it is that there are four layers of the pyramid. As you order the data and organize it in levels up the pyramid, the data transforms into wisdom at the top:

1. You have the data.
2. Managing the data transforms it into information.
3. With more interpretation, that information becomes knowledge.
4. As you use that knowledge and interpret it in the organization’s context, it transforms into wisdom. 

Wisdom is at the top of that pyramid because it is the highest value to the organization. 

So, How Can You Transform Your Data into Wisdom?

Stuart says the successful transformation of data into wisdom starts with setting the right mindset about data. For example, organizations are motivated to care about Customer Experience because it’s what their customers care about, and customer reactions to experiences drive the results at the bottom line. Therefore, it is imperative that those in charge of interpreting data demonstrate that expending resources to this end will lead to better commercial outcomes. Moreover, to make the data’s insights more relatable to people outside the data interpretation field, the data specialist should share them as a story of an individual customer to the rest of the organization. 

Stuart also suggests prioritizing the organization’s key performance indicators (KPI). For example, North Star Metrics should matter the most, and others would fall under that. But, he encourages organizations to have a way that measures Customer Experience that permeates the organization. 

Also, each business unit should measure its progress and collect data. First, the individual unit should consider what inputs to the customer’s experience their team influences. Then, each unit can measure metrics from their efforts at those inputs. From there, the business unit can communicate those insights to demonstrate how their team influences the North Start KPI of the organization. It shows how what they are doing at their input for the experience improves the entire Customer Experience and furthers progress toward those North Start KPIs.  

The fact is, Stuart says, there are points in the customer journey that are more important than other points in the journey regarding customer behavior. Therefore, when it comes to fiscal considerations, you should invest more in specific points than others.

It would help if you were strategic in your measurement. Consider the following questions:

What do we want customers to do, and where should we collect the data? 

What are we going to do with the data we measure? 

How is this information going to roll up into other information we have?

Let’s wrap this up with some practical tips. 

Strategic thinking about data is essential. Too often, we get focused on the tactics on the problems immediately before us. However, the information you collect should serve some more significant North Star KPI for the organization, and it should be something you can influence directly with action.

• Start by thinking about the insights you can produce as an asset to the organization. The wisdom delivered should have a perceived “value” that you can measure. It should have a deliberate process for collection, storage, and availability to people within the organization, like you would with other assets in the company. 
• Compare what you glean now against what you gathered in the past. Every time you go looking for answers in data, you are not starting with a blank slate. You have accumulated knowledge from before. An organization would be remiss in presenting the latest insights without consulting previous findings alongside them. 
• Ensure that you are also updating the lens through which you view the insights. It would be best to look at your interpretations of data through what you know about customer behavior as influenced by concepts from the behavioral sciences. 

We’ve all experienced the unfortunate side effects of too much data. When misinformation reaches the public, it confuses people. Sometimes, it overwhelms them and causes them to focus on the wrong thing. Unfortunately, the same thing can happen within your organization. 

Use Stuart’s data tips to create a data analysis strategy that will deliver the wisdom you need to get the results you want. Otherwise, you might find yourself with a whole bunch of insight about your experience but no idea what it means.

If you have a business problem that you would like some help with, contact me on LinkedIn or submit your pickle here. We would be glad to hear from you and help you with your challenges.

There you have it. No promotions, no gimmicks, just good information. 

We hope you enjoyed this issue of Why Customers Buy. If you have, please forward it to a friend or colleague.

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